Affiliation:
1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China
2. Public Experiment Center, University of Shanghai for Science and Technology, Shanghai, China
Abstract
Aiming at the problem that the current isotropic virtual material-based modeling method for dynamic modeling of sliding joints can hardly reflect the difference between normal and tangential mechanical properties, which restricts the modeling quality, a transversely isotropic material model is introduced to comprehensively describe the mechanical properties of sliding joints. Firstly, a dynamic model based on transversely isotropic virtual material and Deep Neural Network (DNN) is constructed to reflect the relationship between the dynamic parameters of transversely isotropic virtual material [Formula: see text] and the natural frequencies. Then, using the cuckoo search algorithm, the transversely isotropic virtual material parameters are determined. Subsequently, as an application case, the flat and V-guide joints of the M7120D/H surface grinder are employed to validate the proposed modeling method. Finally, compared to the experimental modal test results, the error of natural frequencies is less than 1%, which achieves high accuracy. Additionally, the quantitative comparison based on the same application case shows that the proposed modeling method is superior to isotropic virtual material and spring damping method.
Funder
science and technology commission of shanghai municipality
national natural science foundation of china